The Zebra Pneumothorax device is a software workflow tool designed to aid the clinical assessment of adult Chest X-Ray cases with features suggestive of Pneumothorax in the medical care environment. HealthPNX analyzes cases using an artificial intelligence algorithm to identify suspected findings. It makes case-level output available to a PACS/workstation for worklist prioritization or triage. HealthPNX is not intended to direct attention to specific portions or anomalies of an image. Its results are not intended to be used on a stand-alone basis for clinical decision-making nor is it intended to rule out Pneumothorax or otherwise preclude clinical assessment of X-Ray cases.

Device Description

Zebra's HealthPNX is a radiological computer-assisted triage and notification software system. The software automatically analyzes PA/AP chest x-rays and alerts the PACS/workstation once findings suspicious of pneumothorax are identified.

The following modules compose the HealthPNX software system:

Data input and validation: After a chest x-ray has been performed, a copy of the study is automatically retrieved and processed by the HealthPNX device. Following retrieval of a study, the validation feature assesses the input data (i.e. age, modality, view) to ensure compatibility for processing by the algorithm.

HealthPNX algorithm: Once a study has been validated, the algorithm analyzes the frontal chest x-ray for detection of suspected findings suggestive of pneumothorax.

IMA Integration feature: The study analysis and the results of a successful study analysis is provided to IMA, that notifies the PACS/workstation through the worklist interface.

Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.

The radiologist is then able to review the study earlier than in standard of care workflow.

In summary, the HealthPNX device is intended to provide a passive notification through the PACS/workstation to the radiologists indicating the existence of a case that may potentially benefit from the prioritization. It doesn't output an image and therefore it does not mark, highlight, or direct users' attention to a specific location on the original chest X ray.

The device aim is to aid in prioritization and triage of radiological medical images only.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study details for the HealthPNX device, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

Performance Metric	Acceptance Criteria (Goal)	Reported Device Performance
Detection Accuracy (AUC)	Above 80% (compared to ground truth)	98.3% (95% CI: [97.40%, 99.02%])
Overall Agreement	Not explicitly stated as a separate "goal", but demonstrated high agreement	93.03% (95% CI: [90.66%, 94.95%])
Sensitivity	Not explicitly stated as a separate "goal", but met intended performance	93.15% (95% CI: [87.76%, 96.67%])
Specificity	Not explicitly stated as a separate "goal", but met intended performance	92.99% (95% CI: [90.19%, 95.19%])
Triage Time Reduction	Not explicitly stated, but demonstrated statistically significant reduction	Reduced by 60.93 minutes (from 68.98 mins to 8.05 mins)
Performance Time (Device Analysis to Notification)	Not explicitly stated, but compared to predicate (3.35 mins)	22.1 seconds

2. Sample Size Used for the Test Set and Data Provenance

Sample Size for Test Set: 588 anonymized Chest X-Ray cases (146 pneumothorax positive, 442 pneumothorax negative).
Data Provenance: Retrospective cohort from the USA and Israel.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

Number of Experts: Three (3) US Board Certified Radiologists.
Qualifications: US Board Certified Radiologists. Years of experience are not specified.

4. Adjudication Method for the Test Set

The provided text states that "The validation data set was truthed (ground truth) by three US Board Certified Radiologists (truthers)." It does not explicitly detail an adjudication method like 2+1 or 3+1. This implies that the consensus of these three radiologists established the ground truth, but the specific rules (e.g., majority vote, unanimous) are not described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

Yes, an MRMC-like study was done. The text states: "The triage effectiveness was evaluated by three different US Board Certified Radiologists (readers) that read these cases prospectively in real time with the HealthPNX device (HealthPNX prioritized work-list) and without (standard of care, 'First-in-First-out' or 'FIFO' queue) with a washout period separating between the two read periods with and without the HealthPNX device."
Effect Size of Human Readers' Improvement:
- Without AI (Standard of Care): Mean triage time of 68.98 minutes (95% CI: [60.53, 77.43] minutes).
- With AI (HealthPNX): Mean triage time of 8.05 minutes (95% CI: [5.93, 10.16] minutes).
- Improvement (Reduction): 60.93 minutes. This represents a statistically significant reduction in triage time for time-sensitive images.

6. If a Standalone Study (Algorithm Only) Was Done

Yes, a standalone study was done. The text explicitly states: "The stand-alone detection accuracy was measured on this cohort respective to ground truth." and "Overall, the HealthPNX was able to demonstrate an area under the curve (AUC) of 98.3% (95% CI: [97.40%, 99.02%])".

7. The Type of Ground Truth Used

Expert Consensus: The ground truth for the test set was established by three (3) US Board Certified Radiologists.

8. The Sample Size for the Training Set

The document does not explicitly state the sample size for the training set. It only discusses the validation/test set.

9. How the Ground Truth for the Training Set Was Established

The document does not provide information on how the ground truth for the training set was established. It only describes the process for the validation/test set.

Summary

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Zebra Medical Vision Ltd. % Flair Bar VP Operations Shefayim Commercial Center, PO Box 25 Shefayim, 6099000 ISRAEL

May 6, 2019

Re: K190362

Trade/Device Name: HealthPNX Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer-aided triage and notification software Regulatory Class: Class II Product Code: QFM Dated: April 2, 2019 Received: April 5, 2019

Dear Flair Bar:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for

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devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/CombinationProducts/GuidanceRegulatoryInformation/ucm597488.htm); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm.

For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/) and CDRH Learn (http://www.fda.gov/Training/CDRHLearn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (http://www.fda.gov/DICE) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

For

Thalia T. Mills, Ph.D. Director Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known) K190362

Device Name HealthPNX

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)
X Prescription Use (Part 21 CFR 801 Subpart D)	Over-The-Counter Use (21 CFR 801 Subpart C)

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510 (k) Summary

510(K) Summary - HealthPNX Zebra Medical Vision Ltd.

510(k) Number – K190362

I. Applicant's Name: Zebra Medical Vision Ltd. Flair Bar Shefayim Commercial Center PO Box 25 Shefayim, 6099000 ISRAEL Telephone: +972-9-8827795 Fax: +972-9-8827795
Date Prepared: April 28, 2019
II. Device
Trade Name: HealthPNX

Classification Name:

Radiological Computer Aided Triage and Notification Software

Regulation Number: 21 CFR 892.2080

Classification: Class II, Radiology

Product Code: QFM

III. Predicate Device

The HealthPNX device is substantially equivalent to the following device:

Proprietary Name	cmTriage
Premarket Notification	K183285
Classification Name	Radiological Computer-Assisted Prioritization Software
Regulation Number	21 CFR 892.2080
Product Code	QFM
Regulatory Class	II

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Device Description: IV.

The following modules compose the HealthPNX software system:

HealthPNX algorithm: Once a study has been validated, the algorithm analyzes the frontal chest x-ray for detection of suspected findings suggestive of pneumothorax.

IMA Integration feature: The study analysis and the results of a successful study analysis is provided to IMA, that notifies the PACS/workstation through the worklist interface.

Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.

The radiologist is then able to review the study earlier than in standard of care workflow.

The device aim is to aid in prioritization and triage of radiological medical images only.

V. Intended Use/Indication for Use

VI. Comparison of Technological Characteristics with the Predicate Device

The technological characteristics are compared below.

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TechnologicalCharacteristics	HealthPNX	Predicate: cmTriage(K183285)	Similarities orDifferences
Indication for use	The Zebra Pneumothoraxdevice is a softwareworkflow tool designed toaid the clinical assessmentof adult Chest X-Ray caseswith features suggestive ofPneumothorax in themedical care environment.HealthPNX analyzes casesusing an artificialintelligence algorithm toidentify suspected findings.It makes case-level outputavailable to aPACS/workstation forworklist prioritization ortriage. HealthPNX is notintended to direct attentionto specific portions of animage or to anomalies otherthan Pneumothorax. Itsresults are not intended tobe used on a stand-alonebasis for clinical decision-making nor is it intended torule out Pneumothorax orotherwise preclude clinicalassessment of X-Ray cases	cmTriage is a passive notificationfor prioritization-only, parallel-workflow software tool used byradiologists to prioritize specificpatients within the standard-of-careimage worklist for 2D FFDMscreening mammograms.cmTriage uses an artificialintelligence algorithm to analyze2D FFDM screening mammogramsand flags those that are suggestiveof the presence of at least onesuspicious finding at the examlevel.These flags are viewed by theradiologist via their PictureArchiving and CommunicationSystem (PACS) worklist. Thedecision to use cmTriage codes andhow to use cmTriage codes isultimately up to the radiologist.cmTriage does not send a proactivealert directly to the radiologist.Radiologists are responsible forreviewing each exam on a diagnosticviewer according to the currentstandard of care. cmTriage is limited tothe categorization of exams, does notprovide any diagnostic informationbeyond triage and prioritization, doesnot remove images from theradiologist's worklist, and should notbe used in lieu of full patientevaluation, or relied upon to make orconfirm diagnosis.cmTriage is for prescription use only.	Similar except toanatomy, imagingmodality and lesiontype
Notification-only,parallel workflowtool	Yes	Yes	Same
User	Radiologist	Radiologist	Same
Radiologicalimages format	DICOM	DICOM	Same
Identify patientswith prespecifiedclinical condition	Yes	Yes	Same
Clinical condition	Pneumothorax	Breast Cancer	Different but are"time sensitiveimaging" per 21CFR892.2080
Alert to finding	Passive notification flagged forreview	Passive notification flagged for review	Same
Independent ofstandard of careworkflow	Yes; No cases are removedfrom worklist	Yes; No cases are removedfrom worklist	Same
Modality	X-Ray	FFDM screening mammograms	Different but both runon "radiologicalmedical images" per21 CFR 892.2080
Body part	Chest	Breast	Different anatomicalsites but both"operates onradiological images ofthe human body" per21 CFR 892.2080
ArtificialIntelligencealgorithm	Yes	Yes	Same
Limited toanalysis ofimaging data	Yes	Yes	Same
Aids promptidentification ofcases withindicated findings	Yes	Yes	Same
Where results arereceived	PACS / Workstation	PACS / Workstation	Same

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VII. Performance Data

The HealthPNX has been evaluated and verified in accordance with software specifications and applicable performance standards through Software Development and Validation & Verification Process to ensure performance according to specifications, User Requirements and Federal Regulations and Guidance documents, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices".

The performance of the HealthPNX device has been validated in a pivotal performance study that was carried out in the USA with simulated synthetic work-flow consisting of a truthed validation data-set. The data included a retrospective cohort of 588 anonymized Chest X-Ray cases from the USA and Israel, including pneumothorax positive (n=146) and negative cases (n=442), as well as

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confounding imaging factors. The validation data set was truthed (ground truth) by three US Board Certified Radiologists (truthers). The stand-alone detection accuracy was measured on this cohort respective to ground truth. The triage effectiveness was evaluated by three different US Board Certified Radiologists (readers) that read these cases prospectively in real time with the HealthPNX device (HealthPNX prioritized work-list) and without (standard of care, "First-in-First-out" or "FIFO" queue) with a washout period separating between the two read periods with and without the HealthPNX device.

The detection accuracy met the a-priori performance goal (above 80% level of accuracy compared with ground truth). Overall, the HealthPNX was able to demonstrate an area under the curve (AUC) of 98.3% (95% CI: [97.40%, 99.02%]), which is substantially equivalent to the predicate device, and meets the required performance goal for QFM product code. Additionally, the overall agreement between HealthPNX device and ground truth was 93.03% (95% CI: [90.66%, 94.95%]). The sensitivity and specificity of the HealthPNX was 93.15% (95% CI: [87.76%, 96.67%]) and 92.99% (95% CI: [90.19%, 95.19%])(n=588), respectively.

The HealthPNX reduced triage time as compared to the standard of care (mean time 8.05 minutes (95% CI: [5.93, 10.16] minutes) vs. 68.98 minutes (95% CI: [60.53, 77.43] minutes)(n=588), with the HealthPNX compare to standard of care, respectively). This is a statistically significant reduction of triage time of time sensitive images. This establishes that the HealthPNX meets its intended use statement and is substantially equivalent to the predicate device.

In addition, we assessed the performance time of the HealthPNX that reflects the time it takes for the device to analyze the study and send a notification to the PACS worklist. The average performance time of the HealthPNX was 22.1 seconds, a timing performance that is substantially equivalent to the predicate (3.35 minutes).

VIII. Conclusion

The subject HealthPNX device and the cmTriage predicate device are both software-only devices intended to aid in triage of radiological images, independent of care workflow. The labeling of both devices are limited to the categorization of exams and are not to be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.

Both devices operate in parallel to the standard of care workflow in the sense that they do not change the original image, do not provide any marking, and do not remove cases from the standard of care. The minor differences between the subject device and the predicate raise no new issues of safety or effectiveness. In addition, performance testing demonstrates that the HealthPNX performs as intended . The HealthPNX device is therefore substantially equivalent to the cmTriage predicate.

Regulation Number and Section

§ 892.2080 Radiological computer aided triage and notification software.

(a)
Identification. Radiological computer aided triage and notification software is an image processing prescription device intended to aid in prioritization and triage of radiological medical images. The device notifies a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis of those images performed by the device. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue. The device operates in parallel with the standard of care, which remains the default option for all cases.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (
e.g., improved time to review of prioritized images for pre-specified clinicians).(iii) Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (
e.g., subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment.(iv) Stand-alone performance testing protocols and results of the device.
(v) Appropriate software documentation (
e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results).(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use;
(ii) A detailed description of the intended user and user training that addresses appropriate use protocols for the device;
(iii) Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
e.g., poor image quality for certain subpopulations), as applicable;(iv) A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images;
(v) Device operating instructions; and
(vi) A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (
e.g., improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (e.g., confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.